Intelligent Internet Data Searching

In this thesis author approaches the problem of automated text classification, which is one of basic tasks for building Intelligent Internet Search Agent. The work discusses various approaches to solving sub-problems of automated text classification, such as feature extraction and machine learning on text sources. Author also describes her own multiword approach to feature extraction and pres-ents the results of testing this approach using linear discriminant analysis based classifier, and classifier combining unsupervised learning for etalon extraction with supervised learning using common backpropagation algorithm for multilevel perceptron.

Imaging and Characterisation of Dirt Particles in Pulp and Paper

Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.

Measuring Brand Equity and Analyzing Its Relationship with Key Marketing Mix Elements

The aim of this paper is to analyze the effect of price and advertising on brand equity. The dimensionality of brand equity is thoroughly examined, and the effect price, price deals, perceived advertising spending and advertising appeal have on the dimensions of brand equity are analyzed using multiple regression analysis as well as other supporting analyses. Price and advertising are found to be of great importance to brand equity. Arguably the most influential finding is the strong positive effect low prices – an integral brand element – have on the case company brand equity, even though a negative effect was hypothesized based on prior research. The results also support separating advertising appeal from perceived advertising spending, as well as linking service quality as part of the overall perceived quality in the context of service-intensive firms.

Ohutlevytuotteen valmistuskustannusten määrittely suunnitteluvaiheessa

Diplomityössä kehitetään ABB Oy Drives:lle menetelmää, jolla voidaan ennustaa ohutlevyosien ja niistä koostuvien kokoonpanojen hintaa ilman tarkkaa valmistuksellista geometriatietoa. Työ on osa Tekesin rahoittamaa Piirre 2.0 -projektia. Työn teoriaosa määrittelee lyhyesti ohutlevytuotteet ja niiden valmistusmenetelmät. Laajemmassa teoriatarkastelussa ovat erilaiset ohutlevytuotteiden valmistuskustannusten ennustamismenetelmät regressioanalyysin käyttöön painottuen. Käytännön osiossa määritetään Finn-Power LP6 -levytyökeskuksen suorituskyky ja muodostetaan työaikalaskuri kerättyyn tietoon perustuen. Lisäksi muodostetaan regressioanalyysit kahden eri alihankkijan valmistamien ohutlevytuotteiden pohjalta. Regressiotekniikoiden avulla etsitään kustannuksiin voimakkaasti vaikuttavat parametrit ja muodostetaan laskukaava valmistuskustannusten ennustamiseen. Lopuksi vertaillaan teorian ja käytännön osien yhteensopivuutta ja etsitään syitä havaittuihin eroihin. Tutkimustulosten hyödyntämismahdollisuuksien ohella esitetään myös eräitä jatkokehitysehdotuksia.

Molecular Evolution of Metazoan Hypoxia-inducing Factors

Most metazoans rely on aerobic energy production, which is dependent on adequate oxygen supply. In the case of reduced oxygen supply (hypoxia), the most profound changes in gene expression are mediated by transcription factors named hypoxia-inducible factors (HIF alpha). These proteins are post-translationally regulated by prolyl-4-hydroxylase (PHD) enzymes that are direct “sensors” of cellular oxygen levels. This thesis examines the molecular evolution of metazoan HIF systems. In early metazoans the HIF system emerged from pre-existing PHD oxygen sensors and early bHLH-PAS transcription factors. In invertebrates our analysis revealed an unexpected diversity of PHD genes and HIF alpha sequence characteristics. An early branching vertebrate, the epaulette shark (Hemiscyllium ocellatum) was chosen for sequencing and hypoxia preconditioning studies of HIF alpha and PHD genes. As no quantitative PCR reference genes were available, this thesis includes the first study of reference genes in cartilaginous fish species. Applying multiple statistical analysis we also discoveredthat commonly used reference gene software may perform poorly with some data sets. Novel reference genes allowed accurate measurements of the mRNAlevels of the studied target genes. Cartilaginous fishes have three genomic duplicates of both HIF alpha and PHD genes like mammals and teleost fishes. Combining functional divergence and selection analyses it was possible to describe how sequence changes in both HIF alpha and PHD duplicates may have contributed to the differential oxygen sensitivityof HIF alphas. Additionally, novel teleost HIF-1 alpha sequences were produced and used to reveal the molecular evolution of HIF-1 alpha in this lineage rich with hypoxia tolerant species.

The influence of strategic entrepreneurship on firm performance

In the study the recently developed concept of strategic entrepreneurship was addressed with the aim to investigate the underlying factors and components constituting the concept and their influence on firm performance. As the result of analysis of existing literature and empirical studies the model of strategic entrepreneurship for the current study is developed with the emphasis on exploration and exploitation parts of the concept. The research model is tested on the data collected in the project ―Factors of growth and success of entrepreneurial firms in Russia‖ by Center for Entrepreneurship of GSOM in 2007 containing answers of owners and managers of 500 firms operating in St. Petersburg and Moscow. Multiple regression analysis showed that exploration and exploitation presented by entrepreneurial values, investments in internal resources, knowledge management and developmental changes are significant factors constituting strategic entrepreneurship and having positive relation to firm performance. The theoretical contribution of the work is linked to development and testing of the model of strategic entrepreneurship. The results can be implemented in management practices of companies willing to engage in strategic entrepreneurship and increase their firm performance.

Future revenue models: Transformation from textbooks to digital solutions in the educational publishing industry, Case Sanoma Learning

This study was conducted in order to learn how companies’ revenue models will be transformed due to the digitalisation of its products and processes. Because there is still only a limited number of researches focusing solely on revenue models, and particularly on the revenue model change caused by the changes at the business environment, the topic was initially approached through the business model concept, which organises the different value creating operations and resources at a company in order to create profitable revenue streams. This was used as the base for constructing the theoretical framework for this study, used to collect and analyse the information. The empirical section is based on a qualitative study approach and multiple-case analysis of companies operating in learning materials publishing industry. Their operations are compared with companies operating in other industries, which have undergone comparable transformation, in order to recognise either similarities or contrasts between the cases. The sources of evidence are a literature review to find the essential dimensions researched earlier, and interviews 29 of managers and executives at 17 organisations representing six industries. Based onto the earlier literature and the empirical findings of this study, the change of the revenue model is linked with the change of the other dimen-sions of the business model. When one dimension will be altered, as well the other should be adjusted accordingly. At the case companies the transformation is observed as the utilisation of several revenue models simultaneously and the revenue creation processes becoming more complex.

From network pictures to network insight in solution business – the role of internal communication

Operating in business-to-business markets requires an in-depth understanding on business networks. Actions and reactions made to compete in markets are fundamentally based on managers‘ subjective perceptions of the network. However, an amalgamation of these individual perceptions, termed a network picture, to a common company level shared understanding on that network, known as network insight, is found to be a substantial challenge for companies. A company‘s capability to enhance common network insight is even argued to lead competitive advantage. Especially companies with value creating logics that require wide comprehension of and collaborating in networks, such as solution business, are necessitated to develop advanced network insight. According to the extant literature, dispersed pieces of atomized network pictures can be unified to a common network insight through a process of amalgamation that comprises barriers/drivers of multilateral exchange, manifold rationality, and recursive time. However, the extant body of literature appears to lack an understanding on the role of internal communication in the development of network insight. Nonetheless, the extant understanding on the amalgamation process indicates that internal communication plays a substantial role in the development of company level network insight. The purpose of the present thesis is to enhance understanding on internal communication in the amalgamation of network pictures to develop network insight in the solution business setting, which was chosen to represent business-to-business value creating logic that emphasizes the capability to understand and utilize networks. Thus, in solution business the role of succeeding in the amalgamation process is expected to emphasize. The study combines qualitative and quantitative research by means of various analytical methods including multiple case analysis, simulation, and social network analysis. Approaching the nascent research topic with differing perspectives and means provides a broader insight on the phenomenon. The study provides empirical evidence from Finnish business-to-business companies which operate globally. The empirical data comprise interviews (n=28) with managers of three case companies. In addition the data includes a questionnaire (n=23) collected mainly for the purpose of social network analysis. In addition, the thesis includes a simulation study more specifically achieved by means of agent based modeling. The findings of the thesis shed light on the role of internal communication in the amalgamation process, contributing to the emergent discussion of network insights and thus to the industrial marketing research. In addition, the thesis increases understanding on internal communication in the change process to solution business, a supplier‘s internal communication in its matrix organization structure during a project sales process, key barriers and drivers that influence internal communication in project sales networks, perceived power within industrial project sales, and the revisioning of network pictures. According to the findings, internal communication is found to play a substantial role in the amalgamation process. First, it is suggested that internal communication is a base of multilateral exchange. Second, it is suggested that internal communication intensifies and maintains manifold rationality. Third, internal communication is needed to explicate the usually differing time perspectives of others and thus it is suggested that internal communication has role as the explicator of recursive time. Furthermore, the role of an efficient amalgamation process is found to be emphasized in solutions business as it requires a more advanced network insight for cross-functional collaboration. Finally, the thesis offers several managerial implications for industrial suppliers to enhance the amalgamation process when operating in solution business.

Mathematical modeling of level of anaesthesia from EEG measurements

Problem of modeling of anaesthesia depth level is studied in this Master Thesis. It applies analysis of EEG signals with nonlinear dynamics theory and further classification of obtained values. The main stages of this study are the following: data preprocessing; calculation of optimal embedding parameters for phase space reconstruction; obtaining reconstructed phase portraits of each EEG signal; formation of the feature set to characterise obtained phase portraits; classification of four different anaesthesia levels basing on previously estimated features. Classification was performed with: Linear and quadratic Discriminant Analysis, k Nearest Neighbours method and online clustering. In addition, this work provides overview of existing approaches to anaesthesia depth monitoring, description of basic concepts of nonlinear dynamics theory used in this Master Thesis and comparative analysis of several different classification methods.

The duality of tactical thought : a study of how Swedish land forces' commanders view tactics in irregular warfare

This is a sociological study of the views of officers in the Swedish Army and its Amphibious Forces on tactics in Irregular Warfare (IW), in particular, Counterinsurgency (COIN). IW comprises struggles, where the military weaker part uses an indirect approach with smaller units and integrates the civilian and military dimensions in a violence spectrum including subversion, terrorism, Guerrilla Warfare and infantry actions. IW is the main armed warfare style in insurgencies. COIN is the combined political, military, economic, social and legal actions in counter insurgencies. Data has been collected by means of interviews with almost all (n =43) officers, who were either commanding battalions or rifle and manoeuvre companies while undergoing training for general warfare and international operations. The main theoretical and methodological inspiration is the traditional one for research on social fields, inaugurated by the French sociologist Pierre Bourdieu. The statistical technique used is Multiple Correspondence Analysis. As a background and context base, an inquiry inspired by the Begriffsgechichte (Conceptual History) tradition explores the genesis and development of understandings of the term Irregular Warfare. The research question is outlined as; “how can contemporary Swedish military thought on tactics in Irregular Warfare be characterized using descriptive patterns, mapped in relation to background factors and normative standards? The most significant findings are that there are two main opposing notions separating the officers’ views on tactics in Irregular Warfare: (1) a focus on larger, combat oriented and collectively operating military units versus smaller and larger, more intelligence oriented and dispersed operating units, and (2) a focus on military tasks and kinetic effects versus military and civilian tasks as well as “soft” effects. The distribution of these views can be presented as a two-dimensional space structured by the two axes. This space represents four categories of tactics, partly diverging from normative military standards for Counterinsurgency. This social space of standpoints shows different structural tendencies for background factors of social and cultural character, particularly dominant concerning military backgrounds, international mission experiences and civilian education. Compared to military standards for Counterinsurgency, the two tactical types characterized by a Regular Warfare mind-set stands out as counter-normative. Signs of creative thought on military practice and theory, as well as a still persistent Regular Warfare doxa are apparent. Power struggles might thus develop, effecting the transformation to a broadened warfare culture with an enhanced focus also on Irregular Warfare. The result does not support research results arguing for a convergence of military thought in the European transformation of Armed Forces. The main argument goes beyond tactics and suggests sociological analysis on reciprocal effects regarding strategy, operational art, tactics as well as leadership, concerning the mind-set and preferences for Regular, Irregular and Hybrid Warfare.

Predicting bankruptcy of Finnish limited liability companies from historical financial statements

This master’s thesis studies the probability of bankruptcy of Finnish limited liability companies as a part of credit risk assessment. The main idea of this thesis is to build and test bankruptcy prediction models for Finnish limited liability companies that can be utilized in credit decision making. The data used in this thesis consists of historical financial statements from 2112 Finnish limited liability companies, half of which have filed for bankruptcy. A total of four models are developed, two with logistic regression and two with multivariate discriminant analysis (MDA). The time horizon of the models varies from 1 to 2 years prior to the bankruptcy, and 14 different financial variables are used in the model formation. The results show that the prediction accuracy of the models ranges between 81.7% and 88.9%, and the best prediction accuracy is achieved with the one year prior the bankruptcy logistic regression model. However the difference between the best logistic model and the best MDA model is minimal. Overall based on the results of this thesis it can be concluded that predicting bankruptcy is possible to some extent, but naturally the results are not perfect.

Exploring the feasibility of applying data mining for library reference service improvement : a case study of Turku Main Library

Data mining, as a heatedly discussed term, has been studied in various fields. Its possibilities in refining the decision-making process, realizing potential patterns and creating valuable knowledge have won attention of scholars and practitioners. However, there are less studies intending to combine data mining and libraries where data generation occurs all the time. Therefore, this thesis plans to fill such a gap. Meanwhile, potential opportunities created by data mining are explored to enhance one of the most important elements of libraries: reference service. In order to thoroughly demonstrate the feasibility and applicability of data mining, literature is reviewed to establish a critical understanding of data mining in libraries and attain the current status of library reference service. The result of the literature review indicates that free online data resources other than data generated on social media are rarely considered to be applied in current library data mining mandates. Therefore, the result of the literature review motivates the presented study to utilize online free resources. Furthermore, the natural match between data mining and libraries is established. The natural match is explained by emphasizing the data richness reality and considering data mining as one kind of knowledge, an easy choice for libraries, and a wise method to overcome reference service challenges. The natural match, especially the aspect that data mining could be helpful for library reference service, lays the main theoretical foundation for the empirical work in this study. Turku Main Library was selected as the case to answer the research question: whether data mining is feasible and applicable for reference service improvement. In this case, the daily visit from 2009 to 2015 in Turku Main Library is considered as the resource for data mining. In addition, corresponding weather conditions are collected from Weather Underground, which is totally free online. Before officially being analyzed, the collected dataset is cleansed and preprocessed in order to ensure the quality of data mining. Multiple regression analysis is employed to mine the final dataset. Hourly visits are the independent variable and weather conditions, Discomfort Index and seven days in a week are dependent variables. In the end, four models in different seasons are established to predict visiting situations in each season. Patterns are realized in different seasons and implications are created based on the discovered patterns. In addition, library-climate points are generated by a clustering method, which simplifies the process for librarians using weather data to forecast library visiting situation. Then the data mining result is interpreted from the perspective of improving reference service. After this data mining work, the result of the case study is presented to librarians so as to collect professional opinions regarding the possibility of employing data mining to improve reference services. In the end, positive opinions are collected, which implies that it is feasible to utilizing data mining as a tool to enhance library reference service.